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Data from: A framework for the identification of long-term social avoidance in longitudinal datasets

Citation

Strickland, Kasha et al. (2022), Data from: A framework for the identification of long-term social avoidance in longitudinal datasets, Dryad, Dataset, https://doi.org/10.5061/dryad.tn36j

Abstract

Animal sociality is of significant interest to evolutionary and behavioural ecologists, with efforts focused on the patterns, causes and fitness outcomes of social preference. However, individual social patterns are the consequence of both attraction to (preference for) and avoidance of conspecifics. Despite this, social avoidance has received far less attention than social preference. Here, we detail the necessary steps to generate a spatially explicit, iterative null model which can be used to identify non-random social avoidance in longitudinal studies of social animals. We specifically identify and detail parameters which will influence the validity of the model. To test the usability of this model, we applied it to two longitudinal studies of social animals (Eastern water dragons (Intellegama leseurii) and bottlenose dolphins (Tursiops aduncus) to identify the presence of social avoidances. Using this model allowed us to identify the presence of social avoidances in both species. We hope that the framework presented here inspires interest in addressing this critical gap in our understanding of animal sociality, in turn allowing for a more holistic understanding of social interactions, relationships and structure.

Usage Notes

Funding

National Science Foundation, Award: 1559380, 0918308, 0941487, 0316800